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Overview of energy modeling requirements and tools for future smart energy systems

Author

Listed:
  • Majidi, Hassan
  • Hayati, Mohammad Mohsen
  • Breyer, Christian
  • Mohammadi-ivatloo, Behnam
  • Honkapuro, Samuli
  • Karjunen, Hannu
  • Laaksonen, Petteri
  • Sihvonen, Ville

Abstract

The advancement of technology has led to the development of smart energy systems, integrating traditional and innovative energy solutions with technologies such as IoT and AI. These systems enhance sustainability by diversifying energy sources and enabling sector coupling. To ensure their optimal functionality, precise and comprehensive energy modeling tools are crucial. This paper provides a thorough review of energy modeling tools, focusing on their suitability for future smart energy systems. From the reviewed tools, efficient options are selected based on the requirements of smart energy systems. These systems aim to improve efficiency, resilience, and sustainability while reducing overall energy costs, necessitating innovative modeling solutions. Energy modeling tools play a crucial role in modeling complex energy frameworks, providing insights for informed decision-making. They optimize energy consumption, predict renewable energy variability, facilitate load balancing, and refine resource allocation strategies. However, the evolution of smart energy systems introduces new modeling challenges, requiring the adaptation and updating of the modeling tools. This study identifies the modeling requirements of future smart energy systems and matches them with the capabilities of present tools through a comprehensive comparative analysis.

Suggested Citation

  • Majidi, Hassan & Hayati, Mohammad Mohsen & Breyer, Christian & Mohammadi-ivatloo, Behnam & Honkapuro, Samuli & Karjunen, Hannu & Laaksonen, Petteri & Sihvonen, Ville, 2025. "Overview of energy modeling requirements and tools for future smart energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 212(C).
    • Handle: RePEc:eee:rensus:v:212:y:2025:i:c:s1364032125000401
    DOI: 10.1016/j.rser.2025.115367
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